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How I AI

By Claire Vo

1 recommend/use · 4 sourced episodes

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Productivity4 steps

AI as Your Personalized Just-In-Time Tutor

Feed AI a curriculum tuned to how you learn, then prove understanding by teaching it back.

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Innovation4 steps

AI Rep-Loop Compression

Build AI tools that give you feedback 80% as good as an expert's, on demand, to get years of judgment-building reps in a fraction of the time.

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Self-Mastery3 steps

Behavioral Activation

Act first, then feel better — keep a pre-written list of small actions that reliably reverse a low mood.

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Marketing3 steps

Be The User Reset (Jobs-to-be-Done)

Zoom out and ask what the user hires your product for — then be that user and ask if you'd even buy what you made.

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Leadership4 steps

Broadcast How Leaders Think (Mental-Model Transparency)

Teach your team how key leaders think — not just what they decided — via weekly verbatim-plus-interpretation notes.

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Self-Mastery4 steps

Counterprogram the Narrative (Take a Punch)

When you fear someone thinks less of you, take one small action that proves the opposite instead of litigating the past.

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Self-Mastery4 steps

Cultivate Agency, Not Skills

When AI hands everyone the skills, agency becomes the only differentiator — and you build it by making things.

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Leadership4 steps

Decompose the Strategy You Disagree With Into Hypotheses

Break a plan you doubt into assumptions, find the one you reject, and design the smallest test.

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Communication3 steps

Define Success Before You Prompt

The clearer your definition of success and failure, the better the work you get from people or AI.

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Productivity3 steps

Demos Not Memos

The first 10% of every project is now free — so build something to react to instead of writing documents.

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Innovation3 steps

Design in the Material

PMs and designers should code — not to ship, but to master the material and truly understand what they're designing.

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Leadership3 steps

Diagnose Agent Failure as Structural, Not Stupidity

When an agent does the wrong thing, check its context, tools, and scope — not its intelligence.

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Strategy3 steps

Diagnose With Data, Treat With Design

Data tells you where the problem is; only a creative process tells you how to solve it.

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Self-Mastery4 steps

Dimensionality: Every Strength Is Its Own Weakness

See yourself as infinite dimensions so feedback becomes data, not an identity threat.

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Leadership4 steps

Dissolve the Roles: Build Small Builder Teams

Shrink teams and drop role labels so AI-empowered individuals own the whole problem.

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Communication3 steps

Feedback as a Daily Practice: Opt-In, Check Intention, Name the Difficulty

Make feedback frequent and safe by pre-agreeing to it, checking your motive, and admitting it's hard.

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Leadership4 steps

Goal-Talent-Purpose-Process: Managing People and AI With One Playbook

Treat managing agents like managing people: same four levers, different resources.

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Leadership4 steps

Habit-Formation Model for Team Behavior Change

Drive team adoption (e.g. of AI) with behavioral psychology, not education: consistency, low friction, and a powerful reward loop.

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Communication4 steps

Magic Questions (Statements That End in 'Do You Agree?')

To understand how someone thinks, feed them statements ending in 'is that right?' rather than asking open-ended questions.

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Marketing3 steps

Make the End User Feel Like a Winner

Design agents that don't just do tasks — they make the user look good and feel like a winner.

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Strategy3 steps

Obviously Good, Then Incremental Correctness

Only make obviously good stuff, ship it in iterations, then reconcile the sprawl back to a naked robotic core.

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Productivity3 steps

One Agent Per Lane

Beat context overload by running many narrow, purpose-built agents instead of one do-everything agent.

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Strategy3 steps

Pull the Thread on New Tools

Judge a new AI tool by where it'll be in a week or a month, not where it is on day one.

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Communication3 steps

Ramble-Mode Onboarding

Onboard an AI agent by voice-rambling everything you need, not by wiring up APIs and structured fields.

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Innovation3 steps

Solve the Problem Behind the Problem

When an agent can't do a task, escalate API-to-browser, then reframe to the underlying need it can solve.

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Self-Mastery3 steps

Taste as a Trainable Model

Taste is a virtual machine in your head that predicts whether your in-group will like an idea — built by reps with feedback.

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Leadership3 steps

The Hire-an-Agent Onboarding Model

Set up an AI agent exactly like you'd onboard a human EA: own identity, delegated access, earned trust.

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Innovation3 steps

The Tiny Core Principle

Every enduring product has one tiny thing that is a superpower — find it, protect it, and stop bolting on features.

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Mindset4 steps

You Are Not the Protagonist (Operationalize, Don't Impose)

Your job isn't to convince everyone of your vision — it's to understand the leader's vision and find the spiky places you can shape it.

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